Get the tools you need to use SAS® in clinical trial design!
Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.
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Richard C. Zink, Ph D, is Principal Research Statistician Developer in the JMP Life Sciences division at SAS Institute. He is currently a developer for JMP Clinical, an innovative software package designed to streamline the review of clinical trial data. He joined SAS in 2011 after eight years in the pharmaceutical industry. He is an active member of the Biopharmaceutical Section of the American Statistical Association (ASA), serving as industry co-chair for the 2015 ASA Biopharmaceutical Section Statistics Workshop, and as a member of the Safety Scientific Working Group. He is a member of the Drug Information Association where he serves as Statistics Section Editor for Therapeutic Innovation & Regulatory Science. Richard is a member of Statisticians in the Pharmaceutical Industry, and holds a Ph D in Biostatistics from the University of North Carolina at Chapel Hill, where he serves as an adjunct faculty member. He is author of Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS.
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